TECHNICAL TOOLBOX: Assessing Market Extremes Using Bollinger Bands
Michael Bennett, Optionetics.com
July 24, 2001
July 24, 2001
Want the quickest way to get a bird’s eye view of high volatility on a stock or index without using any numbers? Take a look at Bollinger bands. If you haven’t used them before, they’re well worth your attention. I usually have a basket of stocks I watch at any given time while searching for potentially good trades. Oftentimes the price action in the charts doesn’t really tell me much, and for the most part displays little more than confusion in a market. After all, this is really what a market is: a state of confusion between buyers and sellers, forever doing battle to settle the stock at “fair value.”
One way to gauge entry points on trades is to search for those stocks which are priced at extreme overbought or oversold levels relative to where they’ve been in the past when it appears that either the bulls or the bears are winning the battle. But as with most things, bulls and bears need rest, regardless of who is winning. Hence, you see pullbacks to the moving average in the form profit taking (selling) and short covering (buying) instead of a straight line. This is a good thing, and the reason that patient traders who are cognizant of this fact are often amply more rewarded those who aren’t. That’s why Bollinger bands are such an excellent indicator—perfect for the patient trader’s arsenal. Without such an indicator, even the most patient of traders may be confused as to when to consider pulling the trigger on a buy or sell. But just what are Bollinger bands and how reliable can they be?
When John Bollinger first came up with the idea of the indicator with his namesake, he probably had no idea just how wide its use would reach. Everybody from daytraders to institutional buyers use them to analyze the overbought and oversold conditions of a stock and/or market. Bollinger bands are based on the laws of statistical analysis principles involving what is known as “normal distribution” of data. In our case, the data observed is price data, or what you see on any given price chart for any time frame. In a normal distribution most of the set of data observed lies close to an average or mean. In stocks, this is known as a moving average. The price of a stock will at any given time rise above, fall below, or sit directly upon this moving average that represents the average price of a stock over the course of a given time frame. (For example, the 50-day moving average is the average closing price of a stock over the course of 50 days.)
With stocks, Bollinger bands incorporate the use of standard deviations of the moving average. In the world of statistical jargon, the first standard deviation contains 68% of the price data of the stock, and two standard deviations contain 95% of the price data. To better understand this, look at Figure 1 below of a bell curve representing all of the grades received on a particular exam in a high school history class. In most cases, the first standard deviation of grades will fall somewhere around a grade of “C,” the mean; with 68% of the grades falling between say C- and C+. The next standard deviation contains the “Bs” and “Ds.” It is between a D- and a B+ where 95% of the grades given on the exam fall (two standard deviations from both sides of the mean, or “C”). And finally, there are only a couple of “As” and one or two “Fs”.
Figure 1: A Bell Curve with Standard Deviations
Now applying the same concept to a daily stock chart of Microsoft Corp. (MSFT) with a 20-day moving average (the mean), use each 20 day period as the mean for a set of data for which the Bollinger bands will plot its standard deviations.
Figure 2: MSFT with a 20-day Moving Average
As you can see, the chart doesn’t really tell us much about the trend of the stock, however, when you throw Bollinger bands on top of the price data, you can see the various points at which the stock is overbought and oversold relative to the 20-day moving average.
Figure 3: MSFT with Bollinger Bands
Now, the difference between the Bollinger bands and the history test score example is that Bollinger bands are moving standard deviations. What this means is that the chart plots the two standard deviations above and below the last price bar each day taking into account the mean of the previous 20 days’ prices. After each new trading day, the price data from the 1st day is dropped off and replaced with the new data (hence, the “moving” average). As this occurs, you can see that the bands will converge and diverge as movement in the stock (volatility) increases or decreases over time. This is what makes the Bollinger bands a unique visual gauge of a stock’s volatility. When movement in the stock is less volatile, the bands come together. When the movement of the stock becomes more hyperactive and volatile, the bands will “diverge” or widen.
To understand how Bollinger bands are used, keep in mind that it’s a statistical truth that that all price data will eventually revert back to its mean. So if in fact a stock price pierces through or is resting right around one of the outside bands, the stock is considered “overbought” at the band above the 20-dma and “oversold” at the one below it. We can assume that since the Bollinger bands contain 95% of the price data between the two bands, a piercing of one of them only occurs 5% of the time. Since this is rare, and rare events are what we as patient traders wait for, the next move of the stock is fairly predictable—it’s going to fall back into the 95% group and head toward the moving average once again. This will eventually happen regardless of whether the piercing of the bands is indicative of a continuing trend in the same direction. This isn’t saying that it has to do so overnight, only that it eventually will—most likely sooner rather than later. As a result, we have an opportunity to profit by this phenomenon and the time to put on a trade would be at one of these overbought or oversold extremes.
So what kinds of plays can we place? Now that we understand what Bollinger bands are telling us about a stock’s price action, we can now get a better picture of what kind of play we may want to put on a particular stock. On a breakout, you can choose to wait for the pullback to the mean. Since the piercing on strong volume can indicate a continuation of that trend, waiting for the pullback will allow for the volatility to calm a bit, and allow you to enter a vertical spread with a better entry point at a lower cost, with a more favorable risk/reward ratio.
You might choose to place credit spreads when the stock is piercing one of the two bands with the idea of buying back the spread for a profit when the stock pulls back to the moving average. This is an especially useful strategy when the volatility is high and the bands have diverged quite a bit.
Before placing any options trade, always check the implied volatility and historical implied volatility before deciding on entering a play. Bollinger bands should be used as a visual guide to help screen through the mountains of charts you may encounter when looking for plays.
If you want to save a lot of time when looking for Bollinger band breakouts, you’re in luck if you’re a current Optionetics Platinum subscriber. The site has a rank list scanner in place to search for the top stocks that are breaking out of their Bollinger bands. Once you get your list of breakout candidates, you have the choice to place directional spreads at the breakout or wait for an imminent reversion to the mean. When you do see a pullback, use Platinum to search for the best vertical spreads to take advantage of the most opportune trades going in the direction of the stocks trend. If you’re not a Platinum subscriber, take the two week free trial and check out what you’re missing. The site has been completely revamped and is built for both the novice options trader and the seasoned vet.
Happy Trading!
Michael Bennett
Staff Writer and Trading Strategist
Optionetics.com
mbennett@optionetics.com
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